3) 3D Poses in the Wild (3DPW) [1]}: to test the generalizability of our model, we test on this real-world video dataset. Unfortunately, no real-world multi-class 4D dataset is available. Therefore, we test REDO in a class-specific, , class human, setting using 3DPW. This dataset contains calibrated videos, , known camera, and 3D human pose annotation. However, it doesn't provide ground-truth mesh and depth. To extract a mesh, we fit the provided 3D human pose using the SMPL [2]} template. To compute depth, we use Consistent Video Depth (CVD) [3]} with ground-truth camera data to get temporally consistent estimates. The dataset contains 60 videos (24 training, 12 validation, and 24 testing). During training, we randomly sample clips from all training videos. For evaluation, we evaluate at uniformly sampled clips (10 clips per video) using the validation and test set.
